Need some clarification with statistics

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The discussion revolves around understanding various statistical distributions, including Poisson, binomial, normal, t-student, and chi-square. The original poster seeks clarification on when to use each distribution, emphasizing the importance of grasping fundamental concepts for future learning. Key points include the Poisson distribution being applicable when the average occurrence rate is known over an interval, and the necessity of understanding assumptions related to the data for selecting the appropriate distribution. Participants highlight that there are no fixed rules, and gaining experience with different distributions will enhance intuitive understanding. Overall, the focus is on mastering the basics to prepare for more advanced statistical concepts.
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Im currently doing an introductory stats course and have learnt:

- poisson distribution
- binomial distribution
- normal distribution
- t-student
- and chi-square

I think I know what most of them look like but am having a bit of a hard time distinguishing what distribution to use when faced with questions.

Heres my current understanding:

- poisson distribution - when pop mean is given over an interval?
- binomial distribution - when given sample size and p of success
- normal distribution - n >30 or if normal
- t-student - when population is normal distributed but variance parameter is unknown
- and chi-square - not too sure when to use.

Wondering if anyone can help me with my current problems, thanks in advance!
 
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the normal distrubuted population's random estimated variance is chi square distribute, when you ask what probability you can obtain a variance you need chi square.
 
anjunabeats said:
I think I know what most of them look like but am having a bit of a hard time distinguishing what distribution to use when faced with questions.

Firstly, is the goal here to pass the exam or to learn statistics?
 
bpet said:
Firstly, is the goal here to pass the exam or to learn statistics?

To learn statistics, I am already doing well enough to pass the exam. I am probably going to learn much more difficult concepts in the future so its best if i get the fundamentals right.
 
anjunabeats said:
...its best if i get the fundamentals right.

The key is understanding what assumptions are reasonable for the given data, and which are necessary in order to use a particular distribution in your repertoire. There aren't any fixed rules as to what applies when, but as you learn more distributions and see the various ways they arise you'll gain a more intuitive understanding of which candidates are most suitable for each situation.

Good luck with your studies!
 
bpet said:
The key is understanding what assumptions are reasonable for the given data, and which are necessary in order to use a particular distribution in your repertoire. There aren't any fixed rules as to what applies when, but as you learn more distributions and see the various ways they arise you'll gain a more intuitive understanding of which candidates are most suitable for each situation.

Good luck with your studies!

thanks for pointing out the obvious.
 
anjunabeats said:
thanks for pointing out the obvious.

Glad you appreciate the point - many don't, which is why so much dodgy research gets published.

Regarding the original questions, it sounds like you're on the right track except maybe the Poisson distribution - not sure what you meant by "pop mean is given over an interval", did you mean to say "average occurrence rate is given over an interval"?
 
bpet said:
Glad you appreciate the point - many don't, which is why so much dodgy research gets published.

Regarding the original questions, it sounds like you're on the right track except maybe the Poisson distribution - not sure what you meant by "pop mean is given over an interval", did you mean to say "average occurrence rate is given over an interval"?

Yeah i think i understand poisson distribution more clearly now, just finished the course today probably planning to learn more chunkier stats in the future.
 
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